Investigating the Impact of Electric Vehicle Charging Loads on CSUN's Electric Grid

TL;DR

This study evaluates how increasing electric vehicle charging loads affect the capacity and stability of CSUN's electric grid, providing insights for infrastructure upgrades and future planning amid rising EV adoption.

Contribution

It offers a detailed simulation-based assessment of EV charging impacts on a university's electric grid and explores mitigation strategies involving distributed generation.

Findings

Potential overload risks identified under high EV penetration scenarios

Distributed generation can reduce grid stress from EV loads

CSUN grid model serves as a benchmark for similar studies

Abstract

This paper examines the impact of electric vehicle (EV) charging stations on the capacity of distribution feeders and transformers within the electric grid at California State University Northridge (CSUN). With the increasing adoption of both residential and commercial EVs and the rapid expansion of EV charging infrastructure, it is critical to evaluate the potential overloading effects of intensive EV charging on power distribution systems. This research assesses the impact of EV charging on the operation of CSUN's electric grid, identifying potential overload risks under projected EV adoption scenarios. Detailed simulations and analyses are conducted to quantify the extent of these impacts, focusing on various levels of EV penetration and charging patterns. The study also explores the impact of distributed generation on reducing the stress incurred by EV loads. The findings provide essential insights for utility companies, highlighting the need for strategic upgrades to distribution systems. These insights will help in developing robust strategies for both current operations and future planning to accommodate growing EV charging demands, ensuring grid stability and reliability in the face of increasing electrification of the transportation sector. The modeled CSUN electric grid can be used as a benchmark to study the impact of EV loads in dense areas on various parameters of the grid.